The proposed project will utilize the comprehensive dataset from the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP), a large-scale multi-center study, sponsored by the National Eye Institute, to evaluate the validity of a telemedicine system to identify infants who have sufficiently severe ROP to require evaluation by an ophthalmologist. The specific aims of this proposal do not include the major goals of the e-ROP Study, which have been accomplished already. Instead, the goals of the proposed project involve additional secondary analyses of the e-ROP data to further evaluate the validity of telemedicine for ROP and to refine the system for image evaluation to optimize accuracy and efficiency. The Specific Aims to achieve these goals are: (1) To describe characteristics of image evaluation findings, including the symmetry of ROP features (stage, zone, and plus disease) between paired eyes of infants, the time of their first detection, and the progression of ROP features over time. (2) To describe the characteristics of eyes that were found to have RW-ROP by image evaluation earlier than by diagnostic exam. (3) To evaluate whether the number of ROP evaluations can be reduced based on the risk stratification using a combination of image evaluation and weight gain assessment at the time of imaging. (4) To evaluate whether a single reader system provides equivalent sensitivity and specificity as a system with two readers and adjudication of discrepancies by a third reader, and to describe the characteristics of images that require adjudication. (5) To calculate the sensitiviy and specificity of image evaluation using latent class analysis that considers the clinical diagnostic examination finding as imperfect. The e-ROP dataset is a unique and valuable resource for accomplishing these Aims. The analyses of the image grading results from 7749 image sets of 1257 infants may lead to the development of more accurate and efficient grading protocol for identifying high risk infants for ROP evaluation by an ophthalmologist. The very large sample size, high quality of the dataset, as well as the rich experience and high productivity of the investigators along with the full support of the e-ROP Collaborative Group, support the feasibility and likelihood of high yield of the proposed project.